ft-bert-hcmus-cybersecurity-for-binary-search

This model is a fine-tuned version of bert-base-uncased on the https://www.kaggle.com/datasets/skywardai/network-vulnerability-fixed dataset. It achieves the following results on the evaluation set:

• Loss: 0.0011

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.0221	1.0	50	0.0084
0.0025	2.0	100	0.0015
0.0017	3.0	150	0.0011

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0